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Found 7,413 Skills
Model Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
Code review practices with technical rigor and verification gates. Practices: receiving feedback, requesting reviews, verification gates. Capabilities: technical evaluation, evidence-based claims, PR review, subagent-driven review, completion verification. Actions: review, evaluate, verify, validate code changes. Keywords: code review, PR review, pull request, technical feedback, review feedback, completion claim, verification, evidence-based, code quality, review request, technical rigor, subagent review, code-reviewer, review gate, merge criteria. Use when: receiving code review feedback, completing major features, making completion claims, requesting systematic reviews, validating before merge, preventing false completion claims.
Creates or updates professional-grade agent skills (SKILL.md + optional scripts/references/assets) with strict validation and an iterative generator↔critic workflow. Use when: you want a new skill, want to refactor an existing skill for clarity/token-efficiency, or want to reach an A-grade rubric score.
A comprehensive guide and reference for building agents using LangGraph 1.0, including ReAct agents, state graphs, and tool integrations.
Build AI agents with Subconscious platform. Use when user wants to: build an agent, create an AI agent, use Subconscious, build with TIM, create agent with tools, research agent, search agent, tool-calling agent, subconscious.dev, TIMRUN, tim, tim-edge, timini, tim-gpt, tim-gpt-heavy. Do NOT use for generic OpenAI/Anthropic/LLM tasks without Subconscious.
Reviews and grades an agent skill directory (SKILL.md plus supporting resources) for specification compliance, clarity, token efficiency, safety, robustness, and portability. Use when a user wants a rubric-based critique with a weighted score/grade and concrete, minimal patch suggestions.
Fan-out search across all memory sources when context is unclear or vaguely referenced. Triggers on: 'from earlier', 'remember when', 'what we discussed', 'that thing with', 'the conversation about', 'did we ever', 'what happened with', 'you mentioned', 'we talked about', 'earlier today', 'last session', 'the other day', or any vague reference to past context that needs resolution before the agent can act.
Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering
Launch a sub-agent judge to evaluate results produced in the current conversation
Execute tasks through competitive multi-agent generation, multi-judge evaluation, and evidence-based synthesis
Design, apply, and maintain SKOS taxonomies for joelclaw agent workflows. Use when defining concept schemes, classifying agent inputs/outputs, mapping to external vocabularies, or integrating taxonomy metadata with Typesense retrieval.
Inline risk classification for agent tasks using a 4-tier model. Hybrid routing: GREEN/YELLOW use heuristic file-pattern matching, RED/CRITICAL escalate to war-room-checkpoint for full reversibility scoring.